Shen-Huan Lyu

According to our database, Shen-Huan Lyu authored at least 25 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

CDEoH: Category-Driven Automatic Algorithm Design With Large Language Models.

Yu-Nian Wang, Shen-Huan Lyu, Ning Chen, Jia-Le Xu, Baoliu Ye, Qingfu Zhang

CoRR, March, 2026

On the Learnability of Offline Model-Based Optimization: A Ranking Perspective.

Shen-Huan Lyu, Rong-Xi Tan, Ke Xue, Yi-Xiao He, Yu Huang, Qingfu Zhang, Chao Qian

CoRR, March, 2026

Breaking the Prototype Bias Loop: Confidence-Aware Federated Contrastive Learning for Highly Imbalanced Clients.

Tian-Shuang Wu, Shen-Huan Lyu, Ning Chen, Yi-Xiao He, Bin Tang, Baoliu Ye, Qingfu Zhang

CoRR, March, 2026

Time-Efficient Identifying Key Tag Distribution in Large-Scale RFID Systems.

Yanyan Wang, Jia Liu, Zhihao Qu, Shen-Huan Lyu, Bin Tang, Baoliu Ye

IEEE Trans. Mob. Comput., February, 2026

Interpreting Deep Forest through Feature Contribution and MDI Feature Importance.

Yi-Xiao He, Shen-Huan Lyu, Yuan Jiang

ACM Trans. Knowl. Discov. Data, January, 2026

Compressing model with few class-imbalance samples: An out-of-distribution expedition.

Tian-Shuang Wu, Shen-Huan Lyu, Yanyan Wang, Ning Chen, Zhihao Qu, Baoliu Ye

Pattern Recognit. Lett., 2026

Enhance and reuse: A dual-mechanism approach to boost deep forest for label distribution learning.

Jia-Le Xu, Shen-Huan Lyu, Yu-Nian Wang, Ning Chen, Zhihao Qu, Bin Tang, Baoliu Ye

Pattern Recognit., 2026

Improving multi-label contrastive learning by leveraging label distribution.

Ning Chen, Shen-Huan Lyu, Tian-Shuang Wu, Yanyan Wang, Bin Tang

Pattern Recognit., 2026

A semi-supervised deep forest framework based on margin distribution optimization for tabular data.

Shen-Huan Lyu, Jia-Le Xu, Yi-Xiao He, Yanyan Wang, Baoliu Ye, Qingfu Zhang

Inf. Sci., 2026

2025

Theoretical Investigation on Inductive Bias of Isolation Forest.

Qin-Cheng Zheng, Shao-Qun Zhang, Shen-Huan Lyu, Yuan Jiang, Zhi-Hua Zhou

CoRR, May, 2025

Compressing Model with Few Class-Imbalance Samples: An Out-of-Distribution Expedition.

Tian-Shuang Wu, Shen-Huan Lyu, Ning Chen, Zhihao Qu, Baoliu Ye

CoRR, February, 2025

Enhance learning efficiency of oblique decision tree via feature concatenation.

Shen-Huan Lyu, Yi-Xiao He, Yanyan Wang, Zhihao Qu, Bin Tang, Baoliu Ye

Inf. Sci., 2025

Multi-Range Query in Commodity RFID Systems.

Yanyan Wang, Jia Liu, Zhihao Qu, Shen-Huan Lyu, Bin Tang, Baoliu Ye

Proceedings of the 33rd IEEE/ACM International Symposium on Quality of Service, 2025

Offline Model-Based Optimization by Learning to Rank.

Rong-Xi Tan, Ke Xue, Shen-Huan Lyu, Haopu Shang, Yao Wang, Yaoyuan Wang, Sheng Fu, Chao Qian

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Multi-class imbalance problem: A multi-objective solution.

Yi-Xiao He, Dan-Xuan Liu, Shen-Huan Lyu, Chao Qian, Zhi-Hua Zhou

Inf. Sci., 2024

Personalized Federated Learning with Feature Alignment via Knowledge Distillation.

Guangfei Qi, Zhihao Qu, Shen-Huan Lyu, Ninghui Jia, Baoliu Ye

Proceedings of the PRICAI 2024: Trends in Artificial Intelligence, 2024

Identifying Key Tag Distribution in Large-Scale RFID Systems.

Yanyan Wang, Jia Liu, Shen-Huan Lyu, Zhihao Qu, Bin Tang, Baoliu Ye

Proceedings of the 32nd IEEE/ACM International Symposium on Quality of Service, 2024

Confidence-aware Contrastive Learning for Selective Classification.

Yu-Chang Wu, Shen-Huan Lyu, Haopu Shang, Xiangyu Wang, Chao Qian

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mask-Encoded Sparsification: Mitigating Biased Gradients in Communication-Efficient Split Learning.

Wenxuan Zhou, Zhihao Qu, Shen-Huan Lyu, Miao Cai, Baoliu Ye

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

The Role of Depth, Width, and Tree Size in Expressiveness of Deep Forest.

Shen-Huan Lyu, Jin-Hui Wu, Qin-Cheng Zheng, Baoliu Ye

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

On the Consistency Rate of Decision Tree Learning Algorithms.

Qin-Cheng Zheng, Shen-Huan Lyu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Improving generalization of deep neural networks by leveraging margin distribution.

Shen-Huan Lyu, Lu Wang, Zhi-Hua Zhou

Neural Networks, 2022

Depth is More Powerful than Width with Prediction Concatenation in Deep Forest.

Shen-Huan Lyu, Yi-Xiao He, Zhi-Hua Zhou

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Improving Deep Forest by Exploiting High-order Interactions.

Yi-He Chen, Shen-Huan Lyu, Yuan Jiang

Proceedings of the IEEE International Conference on Data Mining, 2021

2019

A Refined Margin Distribution Analysis for Forest Representation Learning.

Shen-Huan Lyu, Liang Yang, Zhi-Hua Zhou

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019